code: def test_ensembler(
      self, combining_type, search_type, priors, logits, output_graph
  ):
      # Force graph mode
      with tf.compat.v1.Graph().as_default():
          spec = phoenix_spec_pb2.PhoenixSpec()
          spec.ensemble_spec.combining_type = combining_type
          spec.ensemble_spec.ensemble_search_type = search_type
          ensembler_instance = ensembler.Ensembler(spec)
          priors_logits_specs = []
          search_logits_specs = []
          if priors:
              for _ in range(priors):
                  spec = architecture_utils.LogitsSpec(
                      logits=tf.zeros([20, 10])
                  )
                  priors_logits_specs.append(spec)
          if logits:
              spec = architecture_utils.LogitsSpec(
                  logits=tf.keras.layers.Dense(10)(tf.zeros([20, 10]))
              )
              search_logits_specs.append(spec)
          _ = ensembler_instance.bundle_logits(
              priors_logits_specs=priors_logits_specs,
              search_logits_specs=search_logits_specs,
              logits_dimension=10,
          )
          nodes = tf.compat.v1.get_default_graph().as_graph_def().node
          logging.info([node.name for node in nodes])
  
          self.assertCountEqual([n.name for n in nodes], output_graph)
  
file_path: model_search/model_search/ensembler_test.py
imports: from absl import logging
  from absl.testing import parameterized
  from model_search import ensembler
  from model_search.architecture import architecture_utils
  from model_search.proto import ensembling_spec_pb2
  from model_search.proto import phoenix_spec_pb2
  import tensorflow.compat.v2
label_desc: Use image node_id 1 for calling the EnsemblerTest obj's underlying member method code with example usage: obj.test_ensembler(combining_type, search_type, priors, logits, output_graph) without return types